United States     Industrial Environmental Research  EPA-600/7-80-080
Environmental Protection  Laboratory          April 1980
Agency        Research Triangle Park NC 27711
A Case Study in the Use
of Ambient Data for
Source Assessment

R&D Program Report


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                                                  April 1980
        A Case Study in the  Use  of
Ambient  Data for Source Assessment

                 Edward T. Brookman and John E. Yocum

               TRC - The Research Corporation of New England
                      125 Silas Deane Highway
                    Wethersfield, Connecticut 06109
                      Contract No. 68-02-2615
                          Task No. 18
                     Program Element No. INE623
                  EPA Project Officer: John 0. Milliken

                Industrial Environmental Research Laboratory
             Office of Environmental Engineering and Technology
                   Research Triangle Park, NC 27711
                          Prepared for

                  Office of Research and Development
                       Washington, DC 20460


     This report was furnished to the Environmental  Protection Agency by TRC -
THE  RESEARCH  CORPORATION   of New   England,  Wethersfield,  Connecticut,  in
fulfillment of Contract No.  68-02-2615, Task I 18.  The contents  of this report
are reproduced herein as received from the contractor.  The opinions, findings,
and conclusions expressed are those of the author and  not necessarily those of
the Environmental Protection Agency.  Mention of company  or product names is
not to be considered as an endorsement by  the Environmental Protection Agency.


     A common objective  of  regional  environmental  management is to determine
what  sources  of pollution  are the  principal  determinants  of  environmental
quality  in  a  given  area.     This  report  is  a case  history  for such  an
environmental management study that was  conducted  for the  Allegheny  County
Health Department,  Bureau of  Air  Pollution Control  in  Pittsburgh, Pennsyl-
vania. The results of this work were used by Allegheny County as part of their
contribution  to the  State  Implementation  Plan for  achieving  air  quality
standards for total suspended  particulate matter (TSP).   The techniques that
were  utilized  in this  ambient-correlation study  include:   (1)  analysis  of
present  air  quality and trends;  (2)  log-normal distributions;  (3) relative
frequency of TSP levels; (4)  monthly variations in  TSP  levels; (5) weekday/
weekend  analysis;  (6)  wet  day/dry day  analysis;  (7) analysis  of pollution
roses; (8) wind frequency analysis;  (9)  isopleth maps;  (10) contribution of
steel  plant  emissions   by  modeling;   and   (11)  particulate  identification
analysis.  The  integrated application  of these techniques  to  determine the
background traditional  and nontraditional components  of the ambient TSP levels
is described.   The results  of this  environmental  management  study  include
estimates  of  the relative  source  strengths of  particulates,   the relative
impacts of the sources, and the level of confidence of these results.

Disclaimer	iii
Abstract	iv

     1.   Introduction	. ..	. . .  1
     2.   Description of Environmental Management Study  . .... .. .  3
     3.   Methodology Used in Management Study 	  5
          Discussion of Individual Analytical Techniques   ......  5
               Present Situation and Trends  	 	  5
                    Compliance History   	 ......  7
                    Air Quality Trends	 	  7
                    Evaluation of Sampling Sites 	 	  8
               Log-Normal Plots  	 	  8
               Relative Frequency of TSP Levels  	 10
               Monthly Variation in TSP Levels   . .	.10
               Weekday/Weekend Analysis  	 10
               Wet Day/Dry Day Analysis  	 	 13
               Pollution Roses	14
               Wind Frequency Analysis   	 14
               Isopleth Maps of Particulate Patterns   	. . 16
                Contribution of Steel Plant
               Emissions to Selected Monitors ...... 	16
               Particulate Identification Analysis ........... 1.6
          Integrated Application of Techniques   . 	 ... 18
               Background Component  	 	 19
               Traditional and Non-Traditional Components  	 20
     4.   Results of the Management Study	 22
     5.   Critique of the Methodology Used in the Management Study . . 24


Number                                                                Page

   1.     Hi-Vol Monitoring Stations for Allegheny County  ........  6
   2.     Example of Log-Normal Plot for TSP Data	9
   3.     Example of Relative Frequency Plot for TSP Data  	 11
   4.     Example of Seasonal Variation Plot for Two Sampling Sites  . 12
   5.     Example of Integrated Pollution Rose for TSP Data  	 15
 i  6.     Example of Isopleth Map Showing Pattern of TSP Levels
          in ug/m3	17

Number                                                                Page

   1.     Annual Arithmetic Average Component Breakdown For
          Particulate Matter in Allegheny County (1975-1977)  ....    23

                                  SECTION 1


     A frequent task In environmental management for a given region or locality
is to determine what  sources of pollution are the  principal  determinants of
environmental quality in that area.  If this determination can be established
with a reasonable degree of certainty, then the regulatory decisions necessary
to attain compliance with environmental  quality goals for the  area can be made
with minimal  risk.   In  most cases, however,  the determination  of relative
contributions from  the  multitude  of sources  is complicated, especially where
the pollutant is produced from natural  or secondary sources.

     Therefore, one objective of the environmental  manager is  to understand
the relationship between ambient  environmental quality and the  sources which
determine  that  quality.    The  Environmental  Protection  Agency  (EPA)  is
interested  in  analyzing the  various methodologies  that  can be  employed in
accomplishing  this   objective.    Because  any one  methodology may  not  be
universally  suited   to  the  variety of  environmental  management  problems
encountered,  it  is  desired  to  examine  a  typical  study  of ambient-source
correlation where the integrated use of several techniques is employed.  This
report  describes  an  environmental  management study  that TRC-THE  RESEARCH
CORPORATION  of  New  England  conducted  for  the  Allegheny  County  Health
Department Bureau of Air Pollution Control (BAPC)  in Pittsburgh, Pennsylvania,
in which a number of analytical techniques were used to estimate the relative
contributions from various  sources of total suspended particulate (TSP) within
the County.

     This report discusses this management study  in the following manner:

     o    Section 2  describes the scope  of the  environmental management study,
          the results expected, and the users of the study outputs.

     o    Section 3  describes the methodology used  in  the  management study,

          -  present situation and trends
          -  log-normal TSP distribution analysis
          -  relative frequency of TSP  levels
          -  monthly variations in TSP  levels
          -  weekday/weekend analysis
          -  wet day/dry day analysis
          -  pollution roses

-  wind frequency analysis
-  isopleth maps
-  contribution  of  steel plant  emissions to  selected  monitors by
-  particulate identification analysis

The  integrated  application  of  these  techniques  to  determine the
background,  traditional,  and  non-traditional components  of  the
ambient TSP levels is then discussed.

Section 4  describes  the  results  of the management study, including
the  sources of  particulates, the relative impacts of the sources,
and the level  of confidence of the results.

Section  5   presents  a  critique  of  the  methodology  used  in  the
management study and  gives recommendations  that would benefit future

                                  SECTION 2


     Allegheny  County,  Pennsylvania,  has  been  identified  by  EPA  as  a
nonattainment area for TSP that, under the Clean Air Act of 1977, must submit a
revised State  Implementation Plan (SIP)  to EPA describing  how  the National
Ambient  Air Quality   Standards  (NAAQS'S)  for  particulate matter  will  be
achieved by 1982.   TRC was contracted by the  BAPC to organize and manage an
effort  to  develop  strategies  for   the  control  of  traditional  and  non-
traditional  sources  of  suspended particulate matter  in   Allegheny  County.
Several organizations participated in various parts of the project, including
Carnegie  Mellon  University,   U.S.  Steel's  Research  Center,  Energy  Impact
Associates, and Materials Consultants & Laboratories.

     As part of this  management study, several years  of  ambient TSP  data as
measured  by Hi-Volume  Samplers in  the  County were  to  be  analyzed.    The
objective  of  the  analysis  was to use the  available  data to determine  the
relative   contributions   of   industrial    sources   (traditional   and   non-
traditional), non-traditional  sources (such as road  dust)  and background at
selected sites  in the County  that were considered  to be   indicative of  the
particulate problem and that  could  help define  strategies for particulate

     Sulfur  dioxide and  other  specific  gaseous  pollutants  can  usually be
traced to specific sources because they retain their identity from the emission
source, to  the  point  of measurement  in  the ambient  atmosphere.   Analogous
tracking of particulate matter  from source to receptor  is much more difficult,
and often not achievable in practice.   Particulate matter is ubiquitous.  The
particles that are captured on the filter of  a Hi-Vol  can come from a number of
sources and arrive at the point of capture after following innumerable routes.
Furthermore, the range of physical and chemical  properties of particulates are
almost  limitless,  and the use  of  these properties  is  not  a straightforward
means  of  identifying the  sources  and  routes  followed   by  the  collected
particles.  Therefore, a methodology  was  developed to determine  the relative
contributions to  total  particulate matter measured by broad source or  route
classifications  of  particles.   Four classifications  were  considered  as


     Traditional Sources (Industrial)
     In-Plant Non-Traditional Sources
3.   Non-Traditional Sources
4.   Background Material
       Definitions & Examples

"Virgin"  (non-resuspended)  mater-
ial arriving at the sampling point
directly  from  point  and  process
fugitive  sources   within  a  plant

Fugitive  dust  from wind  blown
storage piles and materials handl-
ing  and  resuspended  dust  from
traffic on dusty plant roads.

Dust from construction and  demo-
lition  activities.    Re-entrained
dust  from   road   traffic,   play-
grounds, parking lots,  etc.

Particulate matter of both natural
and anthropogenic  origin  advected
from points outside the County and
over  which  the County  has  no

                                  SECTION 3


     The primary body of data available for the study was that amassed by the
BAPC for the years  1975  through  1977.  During  these  years,  particulate data
were collected  essentially continuously at twenty-four  sampling stations in
the County (Figure  1).   These  particulate  data, together with meteorological
data from the Greater Pittsburgh Airport, were used in  statistical analyses and
manipulations which provided the principal  basis for determining the relative
contributions  of  background,  non-traditional,  and  traditional   sources  of


     The individual analytical  techniques used  in the management study were:

     o    Present situation and trends
     o    Log-normal TSP distribution plots
     o    Relative frequency of TSP levels
     o    Monthly variations in.TSP levels
     o    Weekday/weekend analysis
     o    Wet day/dry day analysis
     o    Pollution roses
     o    Wind frequency analysis
     o    Isopleth maps of particulate patterns
     o    Contribution .of  steel  plant  emissions  to  selected  monitors using
          modeling techniques
     o    Particulate identification analysis

The above methods are described in the following subsections.

Present Situation and Trends

     The development  of  logical  and  effective strategies  for further control
of particulate matter to meet NAAQS's in Allegheny County requires a thorough
understanding  of  trends  in  both emissions  and  ambient concentrations  of
particulate  matter.   Furthermore,   the  siting  of  particulate  monitoring
stations has an important bearing on the levels of particulate matter measured.
Therefore,  this analysis  consisted   of  three  sub-analyses:    a  compliance
history; an analysis of present ambient particulate levels;  and an evaluation
of the present particulate air monitoring stations.

Figure 1.  Hi-Vol Montioring Stations for Allegheny  County.

Compliance History—

     As  a  first  step  in  developing  strategies for  the further  control  of
participate  matter,  it  is  mandatory  to  determine   how  effective  present
regulations have been and are likely to be in reducing particulate emissions.
Allegheny County  has had  in  force  since 1972  a  set  of regulations  for the
control of particulate emissions that  are as  stringent  as any in the country.1
Furthermore, those emission regulations  that  apply to steel making operations,
the  principal  heavy industry in the  County,  represent  levels  of  emission
control that equal or exceed  New Source Performance Standards  for applicable

     A  compliance history was  prepared to show  the  relative   amounts  of
particulate control that  have been achieved roughly to the present  (1976 is the
base year for the emission inventory)  and that are expected to be achieved by
1982 by continued enforcement  of  the requirements of Article XVIII and various
consent decrees.  The beginning  year for this analysis was set as 1971, just
before the enactment of Article XVIII.

     The changes in emissions over the period 1971-1982 have been and will be
the  result  of  installing control  devices,  varying  fuel  mixes,   varying
production  levels, phasing out of old  processes,  the use  of  new processes,
improved maintenance practices,  and other  changes.   The work performed  to
assemble the compliance history was  performed by BAPC personnel.

     The compliance  history showed that there was a 65  percent reduction in
particulate  emissions   between  1971   and  1976  and  that  the  anticipated
reductions in particulate emissions between 1976 and  1982 will be an additional
49 percent.

Air Quality Trends—

     Hi-Vol  sampling is  currently being carried  out  at 24  locations  in
Allegheny County.  Continuous sampling at each of these stations every 3 or 6
days has been  in  progress  since 1975.   Eight of these stations have been in
continuous use since 1970.   The yearly arithmetic and geometric means at each
site  were  computed  and  plotted in  order  to  determine  whether any  large
anomalies exist in the air quality trends at any of the monitoring stations.

     This analysis technique can provide the following types of information:

     o    A large change  in the yearly TSP levels at  only one site can indicate
          a local source starting up or shutting down.  Such a local  source
          could  be  a  construction site,  strip  mine,  or small  industrial
lAllegheny County Health Department Rules and Regulations Article XVIII, June
1972 and Amendments 1978.

     o    A large change in the yearly TSP levels at several sites  in  a  large
          geographical region can  indicate  a major  TSP source starting  up or
          shutting  down  or undergoing a major  change  in  operations.  Such  a
          major source could be a steel plant.

     o    Gradual changes  in the yearly  TSP levels at  a particular site or
          several sites can indicate the effectiveness of implemented control

Evaluation of Sampling Sites—

     To  properly  assess the  representativeness of  the  particulate sampling
stations  to  human exposure, an  analysis  of  each  site should  be performed.
These anlayses  should examine monitor placement, location  of  local sources,
type of neighborhood, etc.  Such an analysis was performed for fifteen of the
Allegheny County sampling sites.  In addition, micro-inventory site  summaries
were performed for an additional eight sampling sites.

     Another way of examining the representativeness  of monitoring sites  is by
using the Standard  Air  Monitoring Work Group  (SAMWG)  guidelines for monitor
placement.2  These  guidelines take  into  account the monitor height, distance
from roads, freedom from airflow obstructions, etc.   This was done for all of
the Allegheny County monitoring stations.

     Based  on  the  SAMWG  guidelines,  observations  were  made  as  to  the
representativeness of the monitoring station  sites chosen  for use in Allegheny
County.   Several of the  sites were felt to be non-representative of the general
TSP levels within the County and were, therefore, not  used in  the subsequent
attainment analysis.

Log-Normal Plots

     An analysis method  that can be useful in determining  the presence of  local
sources is the  log-normal distribution plot in which the percentage of readings
over a certian  TSP level is plotted versus  that TSP level.   If a site is subject
to  large-scale or  general  influences  (i.e.,  many  sources),  then  its TSP
observations should be  log-normally distributed.   If  there  is  a major  local
influence, such as a stack or a strong area source in  a  specific direction from
the sampling site or  some  other  source of extreme  impact, then the data will
either not exhibit log-normality  or  will deviate from it at the plot extremes.
The  facilities  of  the  U.S.  Steel Research  Center  were used to  produce
log-normal plots for  each  of the 24 monitoring  sites  for each  of  the three
study years.  An example of such a plot is given in  Figure 2.
2Air Quality Surveillance Network Design  and  Siting for State Implementation
Plan (SIP) Monitoring.

                              I  I  \  t  t  t  t
10  .50  2.0   10.0  20.0  60.0    90.0
                                                        99.0  99.90  99.99
             Figure  2.  Example of Log-Normal  Plot for TSP Data.
                  (1976 Data For Station 8702-Liberty Boro)

     These plots  showed  that data from  all  stations  appear to be reasonably
log-normally distributed which implies that all  stations  are subject to large-
scale influences.  This result was not expected since several stations  are near
to strong point or area sources.  The log-normal distribution of data for one
station which  recently has  been influenced'  by a nearby  trucking operation
showed only minor deviations from log-normality.

Relative Frequency of TSP Levels

     As in the case of log-normal plots,  a  clue as to whether a monitoring site
is  affected  by  a  single  source  can  be  obtained  by  inspection  of  the
concentration frequency distribution  for that monitor.   If the distribution
shows extreme values of much  larger concentration than the mass of data, then a
directionally dependent effect  on that monitor  or  other similar concentrated
causes for  extreme values may  be  suspected.   Again,  with the  help  of  U.S.
Steel's Research  Center, graphs  of relative frequency were prepared for each
site for each year  of the  study period.   An example of this type of graph is
shown in Figure 3.

     In reviewing  the frequency distribution graphs,  a qualitative judgement
was made as to any evidence  that extreme values might influence the shape of
the distribution  curve.  We  were not  able  to explain why, over the period of
1975-1977, extreme values appear to have an  increasing influence on the pattern
of frequency distributions.

Monthly Variations in TSP Levels

     The three years of TSP data were averaged by month and plotted to show the
monthly and seasonal  variations that exist at each of the  sites.  An abnormally
high winter level can  be an  indication  of  heavy traffic influence due to the
combination of longer morning  inversion  periods, cars idling while cold,  and
road sanding/salting operations.  A high summer level can be an indication of
activity in agriculture or the increased use of school playgrounds.

     A variation of this analysis was  also  performed where the monthly average
plots were  grouped for stations that  are  similar in  character or  in  close
proximity.   This  helps  to  determine  whether  these  groups of  stations  are
influenced by the same source regime.   An  example of this  type of plot is given
in Figure 4.  Note how the  two stations exhibit  similar seasonal TSP patterns,
indicating the  same general  source regime;  while one  station has  a higher
overall TSP level, indicating a local source influence.  These two stations are
within one kilometer of each other.
Weekday/Weekend Analysis

     The arithmetic means for weekday and weekend periods as well as Saturday
and Sunday individually were computed for each site for each  study year and for

       MINIMUM • 3.6000000E+01
       MAXIMUM « 4.3600000E+02
                       RELATIVE FREQUENCY
                            STD. OEV.
                            GEO. MEAN
                     STD. OEV. OF LN.
                                            CUMULATIVE  FREQUENCY
0.0  0.1  0.2  0.3   0.4  0.5  0.6  0.7  0.3  0.9  1.0

 xx xxx xa xxx



       Figure 3.   Example of  Relative  Frequency Plot for  TSP  Data.
                    (1977  Data for Station  5801-County Office Building)

   150  -
••   140  -
E 120

« 110
   100  -
               i   i                           i
                           7570 DUQUESNE 2
                   7502 OUQUESNE 1
            t   i    t    i    t    t

  Figure 4.  Example of Seasonal Variation  Plot  for  Two
                 Sampling Sites. (1975-1977 Data)

all three study years combined.  With only one exception, all of the stations
exhibited lower particulate  levels  on weekends than on  weekdays.   One might
expect  that this  difference  would  be  caused by  a combination  of reduced
industrial activity (traditional  sources)  and reduced traffic (non-traditional
sources) on weekends.  In the Monongahela Valley, which  is dominated by steel
making operations that operate at  a  relatively constant level  every day, one
would expect  that the weekend contributions  from  traditional  sources would
equal those during weekdays.

     Traffic  data could  not  be obtained  at  any  of  the  County monitoring
stations, but some information on traffic patterns was obtained for the state
in general.  These results  were  surprising in  that they showed significantly
more automobile traffic on weekends than  on weekdays.  If the vehicular use in
Allegheny County  is similar  to  that  state-wide,  the average  daily traffic
volume  appears  to  have  a  negative  effect on particulate  concentrations.
However, assuming that traffic resuspends particulate  matter that can affect
Hi-Vol readings, there are  at least  two factors that could  make the traffic
data not consistent with the particulate data:

     1.   Weekend contributions  from  plant  generated fugitive dust  may be
          significantly less than for weekdays.

     2.   Weekend driving patterns are different than those for weekdays.

     During weekends, driving is  done in  the middle  of the day when dispersion
conditions  are  at their  best.   During weekdays, peak  driving  is done in the
early morning  (0630-0900)  and  late  afternoon  (1500-1800)  when  dispersion
conditions may  be poor, thus  keeping traffic-suspended  particulate matter in
the vicinity of the point of generation in a relatively undiluted condition.

     We  were  not able  to  obtain  specific   emission  inventory  data on  a
weekday/weekend  basis,  but  qualitative  reports  from   the  principal  steel
companies in  the  County showed  that,  while steel  production  was relatively
constant throughout  the week, certain operations such as  shipping,  loading,
and  unloading  were  at  reduced  levels  over weekends.   Such  operations  are
important non-traditional  particulate sources.

Wet Day/Dry Day Analysis

     In performing this analysis, it was assumed that on days with sufficient
snow coyer, with greater  than 0.5 centimeters  of precipitation, or following
days  with  greater   than  0.5  centimeters  of   precipitation,   the  principal
contributions to  the TSP  levels  would be traditional sources,  home heating,
vehicle exhaust, and material transported from outside  the  County.  The rain
and snow would  suppress  the majority  of the   local  fugitive  and reentrained
dust.  These days were defined as "wet"  days and all  other days  as "dry" days.
The meteorological data for the three-year study period were examined and the
TSP  levels  at  each  site on wet  days  were then averaged and compared  to the
average TSP levels on the  dry  days.  The results showed that on wet days total

TSP was from 14 to almost 50 percent less than on dry days.  These differences
give a first approximation of the non-traditional source component at each of
the sampling stations.

Pollution Roses

     Pollution roses, which  depict  the average TSP concentration for various
wind directions,  were  constructed using the  computer  facilities of the U.S.
Steel Research Center  for each site for each of the study years.   They were
based on the sixteen compass points for a wind persistence factor >0.71.3 For
each site, two plots were constructed  for each  year:   one for wind" speeds of
0-3.5 m/sec and one for wind speeds of 3.5-20 m/sec.

     To facilitate  subsequent  analyses,  the  data were  then  combined for all
wind speeds and a persistence factor >0.71 and plotted  in accordance with the
eight cardinal  compass  directions.    An example of  this type of plot  is
presented in Figure 5.

     These roses  are useful  in  determining  if high TSP levels are associated
with a particular wind direction  or directions.   They are capable of showing
the following types of influence from sources:

     o    Lack of any specific directional  effect of  sources  on  background

     o    Diffuse influence of distant industrial complexes.

     o    Combination of  diffuse  influence  from distant  sources  and  nearby

     o    Influence of nearby large sources.

Wind Frequency Analysis

     As an aid in performing the analysis,  the percent of time the wind blows
from  a  particular  direction  (persistence   >0.71)  was  determined from  the
Greater Pittsburgh Airport wind data.  This wind  frequency can be  combined with
the pollution rose information to  determine the TSP level contribution from a
particular compass sector.
3Wind persistence factor is defined as the ratio  of vector average wind to the
average wind speed over the 24 hour Hi-Vol sampling period.  A factor near 1.0
indicates a wind that blows consistently from one direction during the entire
sampling period.  A persistence factor  >0.71  is  equivalent to an hourly wind
direction deviation of 45°.

                                                 200  ug/m3
Figure 5.  Example of Integrated Pollution Rose  for TSP  Data.
              (1975-1977 Data for Station 8601 - Glair-ton)

Isopleth Maps of Participate Patterns

     Data for generating  participate  isopleths,  or lines of constant concen-
tration, were developed with the help of the U.S. Steel Research Center.  The
TSP data were stratified  into  periods when wind conditions over the sampling
wind period  met certain  criteria:   wind  direction  within one of  the eight
compass  sectors on  days  with  persistence >0.71  and  within  two  wind speed
classes (0-3.5  m/sec  and  3.5-20 m/sec).   The  average  TSP concentrations for
each site, for  each wind direction,  and for  the two wind speed regimes were
then  combined,   based  on  the  number  of observations,  to  give  the  TSP
concentrations  for each wind direction for  all  wind speeds.  These values were
then  used to   form  isopleth  maps representing  particulate  concentrations
associated with winds from each of the compass directions.  An  example of such
a map  is  presented in  Figure  6.   Recognizing the general  locations  of the
industrial and  urban sources, these isopleth patterns show the effect of wind
"smearing" of these emissions downwind of  the  sources.

Contribution of Steel Plant Emissions to Selected Monitors

     Under the  sponsorship  of  the  steel  companies with  plants  in Allegheny
County, Energy  Impact Associates  (EIA)  of Pittsburgh,  Pennsylvania, carried
out an indepth assessment  of the particulate impact of each  of the steel making
facilities on selected monitors.  The work consisted of the following elements:

     o    Development  of  a  detailed  in-plant particulate  source  inventory
          including emission estimates for fugitive sources.

     o    Development  and  application  of a  model  for  predicting  ambient
          particulate concentrations.   The  model  accounts for particulate loss.
          through deposition.

EIA's calculations were in terms of the yearly arithmetic averages for 1976 and
1982, utilizing  Greater  Pittsburgh Airport winds.  EIA stratified the impact in
terms of point,  process fugitive, and non-traditional sources from within the
plant area.   We  then adjusted the 1976  averages to the three-year average data
base on which our analysis was based by simple ratioing.

Particulate Identification Analysis

     A field sampling program was conducted which collected TSP samples using
membrane type Hi-Vol filters at 12 different  Hi-Vol sites in  the  County.   A
total of  50  samples was  collected including   33  ambient  samples  (21 day,  12
night), 15 control  samples, and 2 special test  filters.   The  sampling was
conducted under carefully specified  wind  and stability  conditions  for each
sampling group by Denardo and McFarland Weather Service, Inc.

     Each ambient  and reference filter was  analyzed  by computer-controlled
Scanning Electron Microscopy/Energy Dispersion  X-Ray Analysis(SEM/EDAX).  This

Figure 6.  Example of Isopleth Map Showing Pattern of TSP Levels
                in ug/m3.   Example is for Southeast Winds.

technique classifies  particles into  various  types.   The  particles  are then
classified as being from  traditional  or non-traditional  sources by comparing
chemistries,  sizes,   and  shapes  of particles  on the  ambient  filters  with
particles from  control  samples taken  from various  industrial  processes,  as
well as from known sources of non-traditional particles such as clay, sand, and
street  dust.    This   analysis was  performed   by  Materials  Consultants  &
Laboratories, Inc. (MCL),  Monroeville,  Pennsylvania.  They provided TRC with
the following information:

     o    The distribution of  particles by  size in  terms of  48 different
          particle chemistries (plus  a miscellaneous category)  for  ambient
          filters collected under specified meteorological conditions and for
          17  reference samples representing  various traditional and  non-
          traditional  sources.

     o    The percentage   by  weight  of  large   particles  (>15  urn)   and  the
          chemistries of such particles.

     o    A  description of  the 49 particle  chemistries   in  terms  of  most
          probable sources, both traditional and non-traditional.

     TRC carried the MCL description of particle chemistries one step further
by  estimating  the relative  percentages  of traditional,  in-plant non-trad-
itional, and urban non-traditional particulate making up each of the particle
chemistries.  These estimates were  then applied  to the results of the filter
analyses made by MCL.   The estimated percentages  were multiplied by the weight
percentages for each of the particle chemistries making up essentially all of
the total weight of the filter catch.  The contributions were then summed and
the resulting percentage breakdown  of traditional, in-plant non-traditional,
and urban non-traditional  components were tabulated for each sample.


     Using the results  of  the  previously described analyses along with other
published information  it was possible to determine the approximate background
TSP  level  for  the County as  well as  the approximate non-traditional  and
traditional components  of  the  mean TSP  level  at each monitoring  site.   The
following subsections  describe the procedures used.

     Before discussing the relative contribution of various components of the
TSP measurement, consideration must be given as to which of the two standards
is the more restrictive:  annual geometric mean of 75 ug/m3 or the short term
standard of  no  more than  one 24-hour  value exceeding 260  ug/m3.   The method
used consisted of computing the standard geometric deviation (SGD) for the data
from each station and  comparing this with the SGD for the standards.  The SGD
of the primary standards  is the slope of the line of a  log-probability plot
passing  through  both  the  24-hour  and  annual  standard.    If  the  SGD  of the
monitor data is  greater than the SGD of the standard, the short-term standard
is more restrictive.   Conversely,  in the SGD of the monitor is less than that
for the standards, the annual  standard  is more restrictive.

     The results of this comparison  showed  that,  with only a few exceptions,
the annual standard was the more restrictive and was therefore used as a basis
for the further analyses.

Background Component

     For  purposes  of developing  a  control  strategy  for  particulate matter,
background concentrations must be taken  into  consideration.  As  used in the
study,  "background concentration"  is  that portion  of the  measured ambient
levels  of particulate  matter  which is  not  attributable to emissions  from
manmade  sources  within  the  County.   This is  essentially material  that is
transported into the study area from external sources over  which the County has
no  control  and  material  generated  within  the  County from  natural  and
agricultural sources.   The mean background  TSP  level  was established through
the use of an "eclectic" particulate  rose and the frequency of wind direction.

     To remove the impact of  Allegheny  County sources  on TSP levels within the
County,  only those wind directions  not  associated with  County  sources  were
chosen  at two selected monitoring  sites  located  at  the far southwest and
northeast edges of the County.  The TSP concentrations at these sites were then
obtained  for all  days  with a  wind persistence  factor  >0.71.   These  were
classified  by wind  direction  sector  and  the mean   of  each data  set was
calculated.   A  composite  (or "eclectic")  particulate rose  was  constructed
utilizing  the wind direction dependent values from the  two sites associated
only with wind directions not associated with County sources.  To determine a
weighted mean background level, the  percent of time  the  wind blew  from each
directional  sector was used.  The  mean  TSP  level for each  directional category
was multiplied by the frequency of wind  from that category  and  the results were
summed for all eight categories in order to give the weighted mean.

     The weighted  values obtained were assumed  to  be  composed of transported
material,  home heating,  vehicle'exhaust, reentrained  road dust,  tire rubber,
and natural  and  agricultural sources.   Since  the  sites  used are  located in
relatively rural or suburban locations  and due to the wind directions chosen,
the contributions  from home heating and  vehicles were  assumed  to  be  quite
small.   Representative  values  for the emissions from these two  sources were
chosen  using published  information.   A background  TSP  level for  Allegheny
County was thus established.  In subsequent analyses, this  background  level was
applied uniformly  to data at all   sampling sites within the County.

     The  background  level developed for  Allegheny County is  51  ug/m3 annual
average  and  48  ug/m3   annual geometric  mean.   These  levels are  high  when
compared  with other urban  areas,  but  considering  the strength  of industrial
sources to the west  and southwest of the  County,  this level of background is
considered reasonable.   Other investigators  using less  rigorous  techniques
have  confirmed  that background levels of  this order  should  be  expected for
Allegheny County.

     One  other  background   value was  computed  in   order  to  provide  some
information on the transported portion of the background level.  It was assumed

that on days with sufficient snow cover, with greater than 0.5 centimeters of
precipitation,  or  following  days  with  greater  than  0.5  centimeters  of
precipitation,  the only  contributors  to  the  Hi-Vol  filter  would  be home
heating, vehicle exhaust,  and transported material from outside the County for
"eclectic" wind directions.  The rain and snow would suppress the fugitive dust
sources.  The meteorological  data for the three-year study period were examined
and those days meeting the above criteria and with wind persistence >0.71 were
noted.  The  TSP  levels  at the background sites were then  obtained for those
particular days, sorted by wind direction,  averaged and weighted as before.

     The  value obtained  was  assumed  to  consist  of  home heating,  vehicle
exhaust, and material transported  from  outside  the County.   As before, using
published  information,  the  combined effects  for  home  heating  and  vehicle
exhaust were estimated.  A value was thus established for the "wet" background
level, or amount due to transport,  in Allegheny County.  This value  is 36 ug/m3
annual average.

Traditional and Non-Traditional Components

     Once the  background  level has  been determined and subtracted  from the
three-year mean, the remainder will be composed of traditional and non-tradi-
tional components.  For the  purposes of the  study, the traditional component
was  assumed  to  be composed  of  industry-related  sources   (stack,  process
fugitive,  and  inplant  fugitives)  and  other fuel  combustion sources  (home
heating) that impact the sampler directly.   The non-traditional component was
assumed to be  composed  of vehicle-related emissions (reentrained  dust, tire
rubber, exhaust, brake linings, etc.), construction-related sources, and other
miscellaneous non-industrial sources.

     To obtain the approximate component breakdown at each site,  a variety of
methods  was  used  which  encompassed any or  all   of  the analyses  described
previously along with other published data calculation methods. The details of
the evaluation at each  site  will  not be described  here  since  they are quite
involved  and  would require   lengthy  explanations.   However,  the  general
methods used will be discussed and some examples will be given.

     Pollution roses were used extensively in the  analyses of the sites.  The
first  step  was  to subtract   the  values  of the  background  rose from  the
site-specific rose.  The  remainder  could then be  examined  in relation to the
directions of  traditional  sources  and  to the directions of  local  non-tradi-
tional  sources  (from  the site  evaluations) and a good  indication  of  the
non-traditional and traditional contributions could be obtained.

     The results of the EIA study were also used extensively.   This  study was a
rigorous treatment of the  impact of steel mill sources on selected monitors and
was considered to be a fair representation  of the  actual  conditions.  A few of
EIA's results were modified where it appeared that part of their contribution
was  more properly  labeled  "non-traditional"  than  "traditional."    The  MCL
results were used as a  check  of the findings of  the EIA near-field modeling

     Direct, day-by-day comparison of TSP levels at various sites resulted in
valuable information on component breakdown.   This was particulary useful at
sites that were  in close  proximity  or that were in very similar geographical
locations.  For example,  it was  seen  that  for wind directions not associated
with the traditional  sources,  the daily TSP levels  at site A were consistently
10-20 ug/m3  higher than the levels at  a neighboring  site  B.   This indicated
that the non-traditional  influence was about 15 ug/m3 higher at site A.

     At several sites,  engineering  judgements were made as to  the effect of
traditional sources.   For  instance,  it was  assumed that two of  the rural sites,
located in the western part of the County, would be  affected identically by the
traditional  sources  within  the  County,   due  to  their approximately  equal
distance from the source  locations.

     The site evaluations were also of  great importance since they indicated
the location and size of  local fugitive dust sources  such  as playgrounds and
parking lots.

     The other analyses, such  as  the seasonal  variations, wet/dry comparisons,
weekday/weekend comparisons,  etc,  were  valuable in providing indications of
whether the non-traditional or traditional  sources predominated.

                                  SECTION 4

                       RESULTS OF THE MANAGEMENT STUDY
     By  the  procedure  outlined  in  the  previous   section,  the  component
breakdown at each site was determined.   The breakdown was calculated both in
terms of arithmetic  and  geometric  means.   The final  results, in terms of the
arithmetic means, are reproduced in Table 1.

  •   An examination  of  this  table reveals  the  relative  contributions of the
traditional and non-traditional  components  of  the  mean TSP levels at each of
the sites within Allegheny County.  It can be seen  that several sites, such as
the  Court  House  (5802)   and Pittsburgh  Airport  (4401),  are  predominantly
affected by traffic  and  other  non-traditional  sources, while others, such as
the Braddock stations (7102  and  7104),  are dominated by traditional sources.
These sites are impacted primarily by the Edgar Thompson Works of U.S. Steel.
Several stations such as  Swissvale (7004)  and Hazelwood 2  (6904), are affected
fairly evenly by both traditional and non-traditional  sources.

     It should be noted  that the values presented in Table 1 are  based on a
wide  variety  of  techniques  plus  a  considerable   amount  of  engineering
judgement.   It  is not possible to assign confidence  levels  in statistical terms
to the values.   However,  we believe that the values are an  accurate assessment
of  the  relative contribution  of  various  sources to particulate  levels in
Allegheny County.  Individual values should not be taken  as firm figures.  The
pollution roses were  generated using airport winds and these have been shown by
EIA to vary considerable  from  local  winds.   There are numerous topographical
features in  Allegheny County  that have  large  effects on airflow patterns.
Nevertheless,  the  patterns  of  contributions  as  a  whole are  a  reasonable
approximation of the true picture and TRC believes they are an adequate basis
for  the  development  of  particulate  control strategies  to meet  air quality
standards by 1982.  Furthermore,  we believe  that the  approach used here, which
relies upon  a  variety of methods and  a considerable amount of  engineering
judgement,  is  a considerable  improvement  over  the  traditional  approach of
using source inventories  together  with unvalidated  models.   To  gain further
insight  as  to  the  exact  components and  their sources  at each  site,  more
detailed studies and measurements are warranted.

                        IN ALLEGHENY COUNTY  (1975-1977)  - ug/m3
Site Location
Logan's Ferry
Greater Pitt. Airport
Murray Towers
Central Lab
County Office Bldg.
Court House
North Fayetta
Hazalwood 1
Hazalwood 2(a)
North 3raddodt(a)
Ouquesne V*'
Ouquesne 2
Allegheny Co. Airport
South Fayette
Coursln Hallow^
' 118
Other Non-Traditional
Stack Trad. Industrial Urban
                                  SECTION 5


     As a means of determining  the  relative contributions of sources for the
development of  control  strategies,  the methodology described  in  this report
has been effective.  The methods used provided  a thorough  understanding of the
nature of the particulate problem in Allegheny County.  The interpretation of
the information developed led to the  isolation of the contributing  sources.  In
particular, the following analyses should be included  in a study of this type:

     o    Trend analyses
     o    Site analyses - these must be done in order to  identify local
          influences that could affect the sampler data
     o    Monthly/seasonal analyses
     o    Pollution roses
     o    Filter analyses

The  other  analyses  that  were  performed were more  useful  as  indicators  of
whether traditional or non-traditional  sources predominated at any particular
site, rather than as methods to  identify  an  individual source.  These analyses

     o    Log-normal plots
     o    Weekday/weekend analyses
     o    Relative frequency plots
     o    Wet day/dry day analyses
     o    Isopleth contours

     While the methodology was effective,  there are several things that should
be  done  to  improve  its usefulness  in  future  studies.    The  following items
should be considered by environmental managers:

     o    The overall placement of particulate samplers should be reviewed in
          relation  to  sources   and  human  exposure,   as  a  means  of  truly
          representing attainment or non-attainment of  air  quality standards
          and providing  adequate geographical coverage  of  the entire study
          area.  Usually,  large  portions  of an area are not covered by sampling
          sites,  while  there  is  considerable   redundancy  of  sampling  in
          so-called "hot spots."

     o    Rather than relying on meteorological  data  from one location, such
          as the nearest airport,  detailed meteorological measurements should
          be recorded simultaneously with the sampler data at each site or at
          least  in  several different  representative  locations.   The  local
          winds  can  vary  significantly from  location  to  location  and  the
          determination of the local wind patterns can greatly help in source

     o    Continuous ISP data should be obtained at several sampler locations
          (i.e., daily, rather than  every third or sixth  day) to allow for the
          influence of traffic,  as well  as providing more detailed information
          on  TSP patterns in  relation  to  meteorological  influences  and
          variations in source strengths.

     o    Traffic flow data  should be obtained concurrently  with  the  TSP
          sampling  data to  allow  for  the correlation between  these  two
          parameters.  The data should be stratified by day  of the week.  This
          would  enable the  weekday/weekend analysis to  be a more  useful
          analytical technique,  and  would also allow a slant distance analysis
          to be performed.*

     o    Information  on  the mixing  depth, or  the  depth  of  the  low-lying
          unstable layer of air below a stable  inversion  layer which limits
          atmospheric  dilution  of  pollutants,  would  be  very  useful   in
          establishing the relationship between inversions and TSP levels.

     o    More statistical analyses,  such  as correlation between particulate
          levels and  variables such  as wind and  other  meteorological  con-
          ditions, could  be  performed  on  the  data   to  establish  confidence

     Two other points to make here that might be of help to the environmental
manager  are  the  use  of  predictive  modeling  and  the  use  of  particle
identification studies.

     o    TRC  feels   that  the  state-of-the-art  of   predictive modeling  is
          inadequate  at  this  time to determine  with   precision  the  relative
          contributions of traditional  and non-traditional  sources  in large
          urban areas.  Attempting to use models  in any  general way based on
          the  currently  available  information  could  lead  to erroneous con-
          clusions and  ill-conceived strategies  for  control of particulate
          matter.   This  statement  is   not applicable  to  situations  where
^Several published studies (e.g.,  National Assessment of the Urban Particulate
Problem.    Volume  I.     National  Assessment.    Lynn,  D.A.,  et.al.,  EPA-
450/3-76-024, July, 1976)  indicate that  there  is a direct relationship between
the daily TSP concentration and average daily level of traffic and an inverse
relationship  between  TSP  and  the distance  of the  Hi-Vol  sampler  from the
traffic, measured by the slant distance.

          sources can be specified in detail  as to configuration, mechanism of
          generation,  and  particle  size  of  emissions;  where the  model  can
          accept and deal with  all  of the above  inputs plus complex terrain;
          and where meteorological  measurements  for  application  of the model
          have been made in  the  near vicinity of sources and receptors.  Such a
          rigorous approach was  used in the special  near-field  study by EIA
          described earlier in this report.

     o    In  this  program,  particle  identification  techniques  were  used to
          establish the source origins  of  various  types  of particles.   While
          such  methods  provide  information  on  the  mechanisms  by  which
          particles are formed,  they do not necessarily show the path by which
          the particles arrived  at  the samplers.  In  developing air  quality
          control strategies,  the path followed by a particle is an important
          factor.   For  example, did the particle  arrive  directly   from  a
          process, or  did  it  deposit  on  the ground  and become  entrained?
          Samples  collected for  particle identification  must  be carefully
          planned, and samples under enough meteorological and source strength
          conditions  must  be  collected   to  be  able to  establish  overall
          contributions of specific sources to a given sampling location.

     The objective of our analysis was to use available data to determine the
relative contributions of industrial  sources  (traditional  and non-tradition-
al), non-traditional sources,  and background at  selected  sites  in  the County
that we believed to be  indicative of the  particulate  problem and  could  help
lead the way to strategies for particulate  control.  The methodology described
in this report has been effective in obtaining this objective.

                                TECHNICAL REPORT DATA
                         (Please read instructions on the reverse before completing)
                                                      3. RECIPIENT'S ACCESSION NO.
A. Case Study in the Use of Ambient Data for
 Source Assessment
            5. REPORT DATE
            April 1980

Edward T. Brookman and John E. Yocum
                                                      8. PERFORMING ORGANIZATION REPORT NO.
TRC—The Research Corporation of New England
125 Silas Deane Highway
Wethersfield, Connecticut  06109
            10. PROGRAM ELEMENT NO.
            11. CONTRACT/GRANT NO.

            68-02-2615, Task 18
 EPA, Office of Research and Development
 Industrial Environmental Research Laboratory
 Research Triangle Park, NC 27711
            Task Final; 5-8/79	
is. SUPPLEMENTARY NOTES ffiRL-RTP project officer is John O. Milliken, Mail Drop 63,
ta. ABSTRACT The report is a case history for an environmental management study to de-
termine what pollution sources are the principal determinants of environmental qual-
ity in Allegheny County, PA. The study was conducted for the Allegheny County
Health Department, Bureau of Air Pollution Control, in Pittsburgh,  PA. Results
were used as part of Allegheny County's contribution to the State Implementation
Plan for achieving air quality standards for total suspended particulate  matter (TSP).
Techniques used in this ambient-correlation study include: (1) analysis of present
air quality and trends; (2) log-normal distributions; (3) relative frequency of TSP
levels;  (4) monthly variations in TSP levels;  (5) weekday/weekend analysis; (6) wet-
day/dry-day analysis; (7) analysis of pollution roses; (8) wind frequency analysis;
(9) isopleth maps; (10) contribution of steel plant emissions by modeling; and (11) par-
ticulate identification analysis. The report describes the integrated application of
these techniques to determine the background traditional and  nontraditional compo-
nents of the ambient TSP levels. Study results include estimates of the  relative
source strengths of the particulates, the relative impacts  of the  sources, and the
level of confidence of these results.
                             KEY WORDS AND DOCUMENT ANALYSIS
                                          b.lDENTIFIERS/OPEN ENDED TERMS
                        c.  COSATI Field/Group
 Pollution Control
 Stationary Sources
 Source Assessment
 Ambient Data

 Release to Public
19. SECURITY CLASS (This Report)

20. SECURITY CLASS (This page)
                         22. PRICE
EPA Form 2220-1 (9-73)